1. Field of the Invention
The present invention relates to an image retrieval apparatus, a control method for the same, and a computer-readable storage medium.
2. Description of the Related Art
Many techniques for retrieving similar images have been proposed. First, there are methods for retrieving similar images using an overall feature amount (global feature amount) of an image. For example, a method has been proposed in which similar images are retrieved utilizing color position information by dividing an image into a plurality of blocks and performing pattern matching using a representative color of each block (Japanese Patent Laid-Open No. 8-249349 (Patent Document 1)). Alternatively, there is also a method in which an image is divided into a plurality of blocks, a feature amount of each block is calculated, and labels according to the feature amounts are given so as to generate a label matrix, which is used as a global feature amount, and similar images are retrieved using the global feature amount (Japanese Patent Laid-Open No. 10-260983 (Patent Document 2)).
Second, methods for retrieving similar images using a localized feature amount (local feature amount) of an image have been proposed. According to these methods, a feature point (local feature point) is first extracted from the image. Next, a feature amount (local feature amount) for the local feature point is calculated from the local feature point and image information in the vicinity thereof. Retrieval of an image is performed by matching local feature amounts.
In the technique using local feature amounts as described above, a method has been proposed in which retrieval is possible even if an image is rotated or enlarged/reduced, by defining a local feature amount as an amount constituted from a plurality of elements that are rotation invariant and enlargement/reduction invariant (C. Schmid and R. Mohr, “Local grayvalue invariants for image retrieval,” IEEE Trans. PAMI., Vol. 19, No. 5, pp. 530-534, 1997) (Non-Patent Document 1)).
However, in the case of methods in which a feature is calculated for each of the blocks into which an image has been divided, and retrieval is performed using features of the entire image (global feature method) as disclosed in Patent Documents 1 and 2, a feature amount will be calculated from an entire query image when performing retrieval. With such methods, there is a problem that retrieval becomes difficult, because the global feature amount changes in the case where, for example, a specific object in an image is clipped, the image is rotated at an arbitrary angle, or the background color of the image is changed.
Further, in the case of a retrieval method using a local feature amount (local feature method), generally, retrieval results are output based on the number of matches between local features or a matching rate thereof. Therefore, there is a problem in that if the number of extracted local feature points is too small, accurate retrieval is often impossible because the number of matches is too small or one incorrect correspondence greatly influences the matching rate.
On the other hand, if the number of local feature points is too large, there is a high possibility of including many unstable local feature points whose reproducibility is low, such as those that may disappear by slightly rotating or enlarging/reducing an image. Such unstable local feature points not only cannot be utilized for image retrieval, but also act as noise, which is the cause of a decrease in the retrieval accuracy.
For that reason, with the method disclosed in Non-Patent Document 1, more stable local feature points are selected by proving a threshold value for the output of a function value utilized when extracting local feature points, so as to discard a local feature point whose value is smaller than or equal to the threshold value, although this is not sufficient.
Furthermore, in addition to the problems in connection with each of the above methods, when the local feature method is added to the existing retrieval system based on the global feature method, obtaining an effect comparable to the cost of adding the local feature method is also a problem.